A prediction method for interior temperature of grain storage via dynamics models: A simulation study. - Di Wang 019; Xi Zhang 006 (CASE, 2015)

Modeling grain quality characteristics via dynamic models using sensing data. - Di Wang 019; Xi Zhang 006 (SII, 2017)

Modeling of a three-dimensional dynamic thermal field under grid-based sensor networks in grain storage. - Di Wang 019; Kaibo Liu; Xi Zhang 006 (IISE Trans., 2019)

Dynamic Field Monitoring Based on Multitask Learning in Sensor Networks. - Di Wang 019; Xi Zhang 006 (Sensors, 2019)

Spatiotemporal Thermal Field Modeling Using Partial Differential Equations With Time-Varying Parameters. - Di Wang 019; Kaibo Liu; Xi Zhang 006 (IEEE Trans Autom. Sci. Eng., 2020)

Spatiotemporal Multitask Learning for 3-D Dynamic Field Modeling. - Di Wang 019; Kaibo Liu; Xi Zhang 006; Hui Wang 035 (IEEE Trans Autom. Sci. Eng., 2020)

A Data Fusion-Based LSTM Network for Degradation Modeling Under Multiple Operational Conditions. - Ying Wang 088; Di Wang 019 (CASE, 2022)

A Generic Indirect Deep Learning Approach for Multisensor Degradation Modeling. - Di Wang 019; Kaibo Liu; Xi Zhang 006 (IEEE Trans Autom. Sci. Eng., 2022)

An Entropy- and Attention-Based Feature Extraction and Selection Network for Multi-Target Coupling Scenarios. - Yuhui Wang 003; Di Wang 019 (CASE, 2023)

A Control Chart for Monitoring Multivariate Spatiotemporal Correlated Data During Grain Storage. - Xingyu Wang; Di Wang 019 (CASE, 2023)

Spatial Rank-Based Augmentation for Nonparametric Online Monitoring and Adaptive Sampling of Big Data Streams. - Xin Zan; Di Wang 019; Xiaochen Xian (Technometrics, 2023)

Distribution-Agnostic Few-Shot Industrial Fault Diagnosis via Adaptation-Aware Optimal Feature Transport. - Ge Yu 005; Di Wang 019; Jinhai Liu; Xi Zhang 006 (IEEE Trans. Ind. Informatics, 2023)

Few-shot RUL Prediction with A Hypernetwork Structure Incorporating Uncertainty Quantification and Calibration. - Ying Wang 088; Fangyu Li; Di Wang 019 (CASE, 2024)

Flexible Degradation Modeling via the Integration of Local Models and Importance Sampling. - Di Wang 019; Andi Wang 001; Changyue Song (IEEE Trans. Instrum. Meas., 2024)

A Latent Variable-Based Multitask Learning Approach for Degradation Modeling of Machines With Dependency and Heterogeneity. - Di Wang 019; Yuhui Wang 003; Xiaochen Xian (IEEE Trans. Instrum. Meas., 2024)

Real-time Cyber-Physical Security Solution Leveraging an Integrated Learning-Based Approach. - Di Wang 019; Fangyu Li; Kaibo Liu; Xi Zhang 006 (ACM Trans. Sens. Networks, 2024)

An Integrated Deep Learning-Based Data Fusion and Degradation Modeling Method for Improving Prognostics. - Di Wang 019; Kaibo Liu (IEEE Trans Autom. Sci. Eng., 2024)

Joint Learning of Failure Mode Recognition and Prognostics for Degradation Processes. - Di Wang 019; Xiaochen Xian; Changyue Song (IEEE Trans Autom. Sci. Eng., 2024)

TCP-ARMA: A Tensor-Variate Time Series Forecasting Method. - Yu An; Di Wang 019; Lili Chen; Xi Zhang 006 (IEEE Trans Autom. Sci. Eng., 2024)

An Adaptation-Aware Interactive Learning Approach for Multiple Operational Condition-Based Degradation Modeling. - Di Wang 019; Ying Wang 088; Xiaochen Xian; Bin Cheng 008 (IEEE Trans. Neural Networks Learn. Syst., 2024)

A Restricted-Learning Network With Observation Credibility Inference for Few-Shot Degradation Modeling. - Ying Wang 088; Fangyu Li; Di Wang 019; Wei Qin (IEEE Trans Autom. Sci. Eng., 2025)

An Adversarial Branched Network for Degradation Modeling Under Multiple Failure Modes. - Di Wang 019; Xinyu Pan; Ershun Pan; Yanting Li (IEEE Trans Autom. Sci. Eng., 2025)

Deep Learning-Based Sensor Selection for Failure Mode Recognition and Prognostics Under Time-Varying Operating Conditions. - Yuhui Wang 003; Andi Wang 001; Di Wang 019; Dong Wang 001 (IEEE Trans Autom. Sci. Eng., 2025)

Distribution-Agnostic Probabilistic Few-Shot Learning for Multimodal Recognition and Prediction. - Di Wang 019; Xiaochen Xian; Haidong Li; Dong Wang 001 (IEEE Trans Autom. Sci. Eng., 2025)

Weakly Supervised Deep Learning for Monitoring Sleep Apnea Severity Using Coarse-Grained Labels. - Xin Zan; Di Wang 019; Changyue Song; Feng Liu 011; Xiaochen Xian; Richard Berry (IEEE Trans Autom. Sci. Eng., 2025)

Partially Observable Online Nonparametric Monitoring of Spatiotemporally Correlated Data Streams. - Di Wang 019; Andi Wang 001; Xiaochen Xian; Yongxiang Li (Technometrics, 2025)